How To Fine Tune An Image Diffusion Model скачать в хорошем качестве

How To Fine Tune An Image Diffusion Model

Link to Colab Notebook: https://colab.research.google.com/git... Link to Exploiting MoE Research Paper: https://arxiv.org/abs/2503.22517 The video provides an overview of diffusion models in AI, covering how they work, how to train them, and the presenter's perspective on their future. Key topics discussed include: How Diffusion Models Work: An explanation of the underlying process, including denoising and reverse diffusion [00:35]. Research and Context: Discussion of a research paper viewing diffusion models through Romanian geometry [00:22] and the history of AI leading to these models [02:28]. Critiques and Future Outlook: The video notes the large size and computational cost of diffusion models [04:04]. The presenter predicts they might become obsolete due to newer models like GPT-4o's image generation capabilities [05:15] and discusses a paper on multimodality in transformers [06:01], ultimately calling diffusion models a "dying technology" [17:53]. Training Guide: A practical walkthrough using a Colab notebook shows how to train a diffusion model, including setup [09:13], fine-tuning tips [11:32], and the role of the Euler method [14:54]. Challenges: The video summarizes difficulties in working with diffusion models, such as expense, lack of user-friendly interfaces, and training complexity [16:59].